In this paper we present a novel approach for digital image noise reduction. Fuzzy Systems and Genetic Algorithms have been already used in image noise reduction, innovation of the proposed method relies on transmission of image pixels into a noise-free environment, also, determination of set fuzzy rules and optimal parameters of this system by utilizing genetic algorithms. Necessity and importance of performing this research work leans on the great demand for new methods that remove noise while preserve details of the original image. In the proposed method, We find median values of eight neighborhood cells of the given image pixels to determine input parameters of the fuzzy system. We also utilize a genetic algorithm to find the set rules and parameters of the membership function of our system automatically and intelligently. Chromosomes of this algorithm are fuzzy rules and parameters of the membership functions. We implemented the proposed filter tested it over standard images. Results reveal the ability of this method in removing noise while preserving details of the image. Logical arguments and experimental results show that the main advantage of this filter is its ability to remove high-density noise.
Aliakbari, S., Ghasemzadeh, M., & Latif, A. M. (2014). A New Fuzzy-Genetic Filter for Digital Image Noise Reduction. Journal of Soft Computing and Information Technology, 3(3), 48-58.
MLA
Somayeh Aliakbari; Mohammad Ghasemzadeh; Ali Mohammad Latif. "A New Fuzzy-Genetic Filter for Digital Image Noise Reduction". Journal of Soft Computing and Information Technology, 3, 3, 2014, 48-58.
HARVARD
Aliakbari, S., Ghasemzadeh, M., Latif, A. M. (2014). 'A New Fuzzy-Genetic Filter for Digital Image Noise Reduction', Journal of Soft Computing and Information Technology, 3(3), pp. 48-58.
VANCOUVER
Aliakbari, S., Ghasemzadeh, M., Latif, A. M. A New Fuzzy-Genetic Filter for Digital Image Noise Reduction. Journal of Soft Computing and Information Technology, 2014; 3(3): 48-58.
)